Search system using images

ABSTRACT

A search system using images is provided in which when a user does not know a relevant URL or search keyword correctly while surfing the Internet, he or she can search a desired website using only an image. The search system using images according to the present invention comprises an image search server and a user terminal. The image search system comprises: an image conversion section for converting the image included in the website information and the to-be-searched image uploaded by the user into search format images; an image search section for comparing eigen values of both the to-be-searched image uploaded by the user and the search image included in the website information and detecting the website information having a matching eigen value; and a storage section for storing the detected website information, the image included in the website information, and information regarding eigen values.

CROSS REFERENCES

Applicant claims foreign priority under Paris Convention and 35 U.S.C.§119 to Korean Patent Application No. 10-2008-0071018, filed Jul. 22,2008, and Korean Patent Application No. 10-2009-0001073, filed Jan. 7,2009, with the Korean Intellectual Property Office, where the entirecontents are incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a search system using images in whichwhen a user does not know a relevant URL or search keyword correctlywhile surfing the Internet, he or she can search a desired website usingonly an image.

2. Background Art

In general, when Internet users want to search for desired informationon the Internet, they drive a web browser for Internet access and thenenter an URL address for a specific domain in an URL entry window todirectly gain access to a website to be searched, or gains access to aspecific portal search site and then enter a specific keyword, asentence or the like indicating desired information in a search boxprovided by the search site so as to search for the desired information.

In this case, a method of using the URL address is one in which after auser has memorized or recorded alphabet characters indicative of URLinformation, he or she directly types them in an URL entry window so asto connect to a desired website. Also, a method of using the keyword isone mainly used when a user does not know a correct domain and isadvantageous in that the user can freely search for desired informationin an enormous amount of data.

However, among the aforementioned conventional methods for searching forinformation on the Internet, the method of using the URL address entailsa problem in that when the user forgets the URL indicating a specificdomain or loses the recorded information, he or she must spendconsiderable time finding the domain.

In addition, the method of searching for information using a keyword onthe Internet encounters a problem in that when the user does not know acorrect keyword indicative of information to be searched, he or she doesnot easily find the associated information.

That is, the conventional information search method has a problem inthat when a user does not know an associated URL information or akeyword for searching a specific website, much time is spent to searchfor information on the Internet and is not provided with an alternativesearch method.

SUMMARY OF THE INVENTION

Accordingly, the present invention has been made in an effort to solvethe aforementioned problems occurring in the prior art, and it is anobject of the present invention to provide a search system using imagesin which when a user does not know a relevant URL or search keywordwhile surfing the Internet, he or she can search a desired website usingonly an image.

Another object of the present invention is to provide a search systemusing images, which can identify information of matching or similarimages considering an error through the adjustment of the degree ofsimilarity between images of various different angles, colors and sizewith respect to search images.

To accomplish the above objects, according to the present invention,there is provided a search system using images comprising an imagesearch server for searching for an image included in websiteinformation, and a user terminal for allowing a user to register andupload a to-be-searched image in the image search server, wherein theimage search system includes: an image conversion section for convertingthe image included in the website information and the to-be-searchedimage uploaded by the user into search format images, the imageconversion section including a unit color management module forextracting the number of and the ratio between unit colors included inboth the image included in the website information and theto-be-searched image uploaded by the user, as eigen values; an imagesearch section for comparing an eigen value of the to-be-searched imageuploaded by the user, which has been extracted in the image conversionsection 120 with an eigen value of the search image included in thewebsite information, which has been extracted in the image conversionsection, and detecting the website information having a matching eigenvalue; and a storage section for storing the detected websiteinformation, the image included in the website information, andinformation regarding eigen values for the converted search formatimages.

Preferably, the image conversion section further includes anon-compression format conversion module for converting the imageincluded in the website information and the to-be-searched imageuploaded by the user into non-compression format images.

Preferably, the image conversion section further includes a collectiveregion management module for extracting the number of colors and adegree of collection for the ratio between the colors at a certainregion formed by collecting pixels in a similar relation among unitcolors included in both the image included in the website informationand the to-be-searched image uploaded by the user, as eigen values.

Preferably, the image conversion section further includes arepresentative color management module for reducing the image includedin the website information and the to-be-searched image uploaded by theuser at an arbitrary fixed ratio, reconstructing each of the reducedimages in a representative color among the colors of respective pixelsbased on an arbitrarily simplified color palette, and extracting thereconstructed representative color as the eigen value.

Preferably, the image conversion section further includes alinear/multi-linear pattern management module for extracting thelinear/multi-linear pattern information between single/plural patternsin the pattern unit as the eigen value based on the value designated tothe color of each pixel in the image included in the website informationand the to-be-searched image uploaded by the user in the case where thevalues of a linear or multi-linear pattern (a face defined by aplurality of lines adjacent to each other or a plurality of lines notadjacent to each other) of pixels, or the colors in a similar andspecific relation are adjacent to each other in a pixel unit.

Preferably, the image conversion section further includes a hash valuemanagement module for extracting a hash value for an initial file of theimage included in the website information and the to-be-searched imageuploaded by the user as an eigen value.

Preferably, the image search section further includes an entire/partialmatching selection module for adjusting an error range for a comparisonresult of the compared eigen values.

Preferably, the image search server further includes: a web servicesection for providing an Internet access service and then transmittingwebsite information including a search image, in which theto-be-searched image of a user is registered, to the user terminal toallow the user terminal to output the transmitted website information;and a search engine for searching for the website information.

Preferably, the image search server comprises a search image registeringinterface screen for allowing the user terminal connected theretothrough the Internet to register the search image.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, features and advantages of the presentinvention will be apparent from the following detailed description ofthe preferred embodiments of the invention in conjunction with theaccompanying drawings, in which:

FIG. 1 is a block diagram illustrating a search system using images oneembodiment of the present invention;

FIG. 2 is a detailed block diagram illustrating a image search server ofFIG. 1;

FIG. 3 is a view illustrating color simplicity;

FIG. 4 is a view illustrating a concrete example of information on thenumber of colors;

FIG. 5 is a view illustrating conversion of the unit colors for anon-compression format image, a reduced file image and a colorsimplified image into an eigen value;

FIG. 6 is a view illustrating a linear pattern compared by a linearpattern comparison module;

FIG. 7 is a flow chart illustrating a search processing method performedby the search system using images according to the present invention;

FIG. 8 is a photographic view illustrating an image included in a searchweb page information;

FIG. 9 is a photographic view illustrating two images for use in theentire matching determination for the eigen values;

FIG. 10 is a photographic view illustrating two images for use in thepartial matching determination for the eigen values, which images arethe same as in terms of size but are different from each other in termsof color information;

FIG. 11 is a photographic view illustrating two images for use in theentire matching determination for the linear/multi-linear patterninformation when the search image is a part of the to-be-searched image;and

FIG. 12 is a photographic view illustrating two images for use in thepartial matching determination for the linear/multi-linear patterninformation when the search image is a part of the to-be-searched imageand the search image and the to-be-searched image are different fromeach other in terms of color.

DETAILED DESCRIPTION

Reference will now be made in detail to the preferred embodiment of thepresent invention, examples of which are illustrated in the drawingsattached hereinafter, wherein like reference numerals refer to likeelements throughout. The embodiments are described below so as toexplain the present invention by referring to the figures.

Now, the present invention will be described in more detail hereinafterwith reference to the accompanying drawings.

FIG. 1 is a block diagram illustrating a search system using images oneembodiment of the present invention, and FIG. 2 is a detailed blockdiagram illustrating an image search server of FIG. 1.

As shown in FIG. 1, an image search server 100 searches for websiteinformation from website servers 400 connected to a communicationnetwork, and then perform an image conversion on the searched websiteinformation and stores the image conversion result. Also, after theimage search server 100 connects to the communication network 300, itreceives an image to be searched (hereinafter, referred to as“to-be-searched image”) from a user terminal 200 such as a mobilecommunication terminal 210, a user computer 220 or the like which can beconnected to the Internet to perform an image conversion on the receivedimage, and searches a registered image which matches the to-be-searchedimage so as to provide a variety of information. In this case, theto-be-searched image is an image which is directly registered from theuser terminal or may include all kinds of images which can be displayedin a web browser.

The image search server 100 will be discussed hereinafter in more detailwith reference to FIG. 2.

As shown in FIG. 100, the image search server 100 includes a web servicesection 110 for providing an Internet access service and thentransmitting website information including a search image, in which ato-be-searched image of a user is registered, to a user terminal toallow the user terminal to output the transmitted website information;an image conversion section 120 for converting an image included inregistered website information and a search image uploaded andregistered by the user into search format images; an image searchsection 130 for comparing the search image uploaded by the user whichhas been converted in the image conversion section 120 with the searchimage included in the registered website information which has beenconverted in the image conversion section, detecting the websiteinformation from an image corresponding to the to-be-searched imageuploaded by the user, and outputting the detected website information tothe web service section 110 of the image search server 100; and astorage section 140 for storing the detected website information andinformation regarding the search format images converted in the imageconversion section 120.

The web service section 110 can be implemented by a server systemprogram for providing an Internet service such as IIS, Apache web serverand the like. Also, an interface provided by the web service section 110includes a search image registering interface screen for registering asearch image using the user terminal connected thereto through theInternet. The search image registering interface screen allows forregistration of the search image through an upload by a search imagefile name and a drag and drop of a corresponding search image on amonitor of a user terminal. In this case, the search image registeringinterface screen may be configured such that the user can input errorinformation set arbitrarily.

Also, the image conversion section 120 includes a non-compression formatconversion module 121, a unit color management module 122, a collectiveregion management module 123, a linear/multi-linear pattern managementmodule 124, a representative color management module 125 and a hashvalue management module 126.

The non-compression format conversion module 121 converts the imageincluded in the website information and the to-be-searched imageuploaded by the user into non-compression format images. In this case,the non-compressed file format converted by the non-compression formatconversion module 121 means conversion of a compression file format ofjpg files, etc., into a non-compression file format of bmp files, etc.The eigen value for an image refers to an annotated tag or linkinformation for a corresponding website and is stored in the storagesection 140.

The unit color management module 122 extracts the number of and theratio between unit colors included in both the image included in thewebsite information and the to-be-searched image uploaded by the user aseigen values. For example, as a unit color value representative of theunit color, red color can be designated as “1”, green color can bedesignated as “2” and blue color can be designated as “3”, arbitrarilyrespectively. A pixel-unit image as shown in FIG. 4 can be changed to avalue representing each color as shown in FIG. 5. That is, in FIG. 4,assuming that each square is a pixel, an image consisting of 24(=6×4)pixels includes five red pixels, eight blue pixels and eleven greenpixels. Each color number information is used as an eigen value forimage search.

The collective region management module 123 extracts the number ofcolors and a degree of collection for the ratio between the colors atcertain regions which are adjacent to or separate from each other in theimage, as eigen values. For example, in the case where the colors ofpixels at a specific region in the image are arranged in this order ofred, red, blue and yellow and the colors of pixels at a region spacedapart by a given distance from the specific region are arranged in thisorder of green, green and blue, these information is used as the eigenvalue.

In the case where the values of a linear or multi-linear pattern (a facedefined by a plurality of lines adjacent to each other or a plurality oflines not adjacent to each other) of pixels, or the colors in a similarand specific relation are adjacent to each other in a pixel unit, thelinear/multi-linear pattern management module 124 extracts thelinear/multi-linear pattern information between single/plural patternsin the pattern unit as the eigen value based on the value designated tothe color of each pixel in the image included in the website informationand the to-be-searched image uploaded by the user.

The representative color management module 125 reduces the imageincluded in the website information and the to-be-searched imageuploaded by the user at an arbitrary fixed ratio, reconstruct each ofthe reduced images in a representative color among the colors ofrespective pixels based on an arbitrarily simplified color palette, andextracts the reconstructed representative color as the eigen value. Inthis case, the reduction of the images means the reduction of imagesfile at a specific ratio, and the reconstruction of the images in therepresentative color means the conversion of the color of each pixelinto an arbitrary representative color determined depending on a changein spectrum of HSV. For example, the reconstruction of therepresentative color is a change of the color palette according tosaturation, brightness and the like. In this case, a variety of methodscan be applied including a method in which a color is changed into adeeper or lighter color or an image is changed into while/black color,sepia-tone color, red color, yellow color, blue color or the like tosimplify the color. That is, as shown in FIG. 3, five colors in the36-color palette can be represented as one representative color which isyellow in the 16-color palette. The thus converted representative colorscan be used such that each color is indicated by a specific numberlater.

The hash value management module 126 extracts a hash value for aninitial file of the image as an eigen value. The hash value is generatedby various kinds of formats besides CRC, MDS and SHA-1. The hash valuemanagement module 126 generates a unique eigen value for each initialfile, and the eigen value is typically represented in the form of“dkfj354k5k6lkdkf”. In this case, even when a modification is made ononly a part of any data file, this hash value becomes a completelydifferent one. But when the modified part of the data file returns toits original state, the hash value again becomes an original hash value.

The storage section 140 annotates (tags or links) the websiteinformation searched by a search engine (not shown) or the like, theimage converted into each non-compression file format by thenon-compression format conversion module 121 and the unit colormanagement module 122 of the image conversion section 120, a searchformat image such as a reduced file image and a color simplified imageof the image converted into the non-compression format, the hash valueinformation as the eigen value information, information on the number ofand the ratio between unit colors, and the linear/multi-linear patterninformation for the purpose of search of websites, and stores theannotated items of information along with the website information. Thatis, the storage section 140 annotates (tags or links) the eigen valuecorresponding to each file and stores the annotated eigen value alongwith the website information, so that a user can search a correctlymatching image file at the speed of search level by means of an existingtext.

In the meantime, the image search section 130 includes a unit colorcomparison module 131, a linear/multi-linear pattern comparison module132, a collective region comparison module 133, a representative colorcomparison module 134, a hash value comparison module 135, and anentire/partial matching selection module 136. In this case, therespective comparison modules can increase search efficiency by alone ora combination of two or more thereof.

The unit color comparison module 131 compares the eigen values extractedby the unit color management module 122 for the number of and the ratiobetween the unit colors included in both the image included in thewebsite information and the to-be-searched image uploaded by the user,and determines whether or not the compared eigen values match eachother.

The linear/multi-linear pattern comparison module 132 compares the eigenvalues of the linear/multi-linear patterns extracted by thelinear/multi-linear pattern management module 124 for the image includedin the website information and the to-be-searched image uploaded by theuser, and determines whether or not the compared eigen values match eachother.

The collective region comparison module 133 compares the eigen values ofthe collective regions extracted by the collective region managementmodule 123 for the image included in the website information and theto-be-searched image uploaded by the user, and determines whether or notthe compared eigen values match each other.

The representative color comparison module 134 compares the eigen valuesof the representative colors extracted by the representative colormanagement module 125 for the image included in the website informationand the to-be-searched image uploaded by the user, and determineswhether or not the compared eigen values match each other.

The hash value comparison module 135 compares the eigen values of thehash values extracted by the hash value management module 126 for theimage included in the website information and the to-be-searched imageuploaded by the user, and determines whether or not the compared eigenvalues match each other.

The entire/partial matching selection module 136 is provided to adjustan error range for the comparison results of the respective eigen valuescompared by the comparison modules 131 to 135 of the image searchsection 130. The user can arbitrarily set an “accuracy setting” itemthrough the entire/partial matching selection module 136 during thesearch.

In the case where the image search section 130 searches for the websiteinformation including the search image uploaded, it annotatesinformation regarding a corresponding website to the website informationstored in the storage section to store the annotated information in thestorage section, and outputs the annotated information to the userterminal, so that the user can perform a keyword search for acorresponding information later.

FIG. 7 is a flow chart illustrating a search processing method performedby the search system using images according to the present invention.

As shown in FIG. 7, the search processing method performed by the searchsystem using images according to the present invention including the webservice section, the image conversion section and the image searchsection includes an image conversion process (S10) in which the imageconversion section 120 converts an image included in the websiteinformation, which is searched on the Internet and is stored into asearch format image to store the converted search format image, andconverts a to-be-searched image uploaded by the user into a searchformat image, and a website search process (S20) in which the imagesearch section 130 compares the image of the website information and theto-be-searched image uploaded by the user, which are converted into thesearch format image, and searches for the website information includingthe to-be-searched image uploaded by the user.

In the image conversion process (S10) of the above-mentioned searchprocessing method, a website information search step (S11) is performedin which website information provided on the Internet is searched forand the searched information is stored as shown in FIG. 7.

Also, the image included in the website information searched in thewebsite information search step (S11) is extracted (S12) and theextracted image is subjected to image conversion (S13).

In this case, the image conversion performed in the step S13 includesthe steps of: converting the image included in the searched websiteinformation into a search format image; extracting a hash value from theconverted search format image as an eigen value; extracting the numberof unit colors and the ratio between the unit colors as eigen values;extracting the number of unit colors and the ratio between the unitcolors at a certain collective region as eigen values; extracting thelinear/multi-linear pattern information as an eigen value; andreconstructing a reduced image in a representative color among thecolors of respective pixels and extracting the reconstructedrepresentative color as an eigen value.

In this case, the non-compression format image conversion refers toconversion of the image included in the website information, which haspreviously searched and stored, and the to-be-searched image uploaded bythe user into a non-compression format image by the non-compressionformat conversion module 121 of the image conversion section 120.

Also, the extraction of the hash value from the converted search formatimage as the eigen value refers to extraction of a hash value for aninitial image file from the image included in the website informationand the to-be-searched image uploaded by the user as an eigen value.

In addition, the extraction of the number of unit colors and the ratiobetween the unit colors as the eigen values refers to the extraction ofthe number of and the ratio between the unit colors included in both theimage included in the website information and the to-be-searched imageuploaded by the user as eigen values by the unit color management module122.

Further, the extraction of the number of unit colors and the ratiobetween the unit colors at a certain collective region as eigen valuesrefers to extraction of a degree of collection for the number of colorsand the ratio between the colors at certain regions which are adjacentto or separate from each other in the image included in the websiteinformation and the to-be-searched image uploaded by the user as aneigen value by the collective region management module 123.

Besides, the extraction of the linear/multi-linear pattern informationas the eigen value refers to that in the case where the values of alinear or multi-linear pattern, or the colors in a similar and specificrelation are adjacent to each other in a pixel unit, thelinear/multi-linear pattern management module 124 extracts thelinear/multi-linear pattern information between single/plural patternsin the pattern unit as the eigen value based on the value designated tothe color of each pixel in the image included in the website informationand the to-be-searched image uploaded by the user.

Furthermore, the reconstruction of the reduced image in therepresentative color among the colors of the respective pixels andextracting the reconstructed representative color as the eigen valuerefers to that the representative color management module 125 reducesthe image at an arbitrary fixed ratio, reconstruct the reduced image ina representative color among the colors of the respective pixels basedon an arbitrarily simplified color palette, and extracts thereconstructed representative color as the eigen value.

Since the extraction steps of the eigen values has been described abovein detail with reference to FIGS. 1 to 6, its detailed description willbe omitted.

Next, after the above-mentioned image conversion has been performed, theconverted image and the eigen values are annotated to the correspondingwebsite information stored in the storage section and are stored in thestorage section.

The above-mentioned steps S11 to S14 is referred to as the imageconversion process (S10).

Subsequently, after the image conversion process (S10) has beenperformed, the website search process (S20) of searching for websiteinformation using the to-be-searched image uploaded by the user will bedescribed hereinafter.

In the step S21 of the website search process (S20), as shown in FIG. 7,after a user who desires to retrieve information gains access to theimage search server 100 using the user terminal 200, he or sheregisters, a search image corresponding to website information to besearched, on an interface screen provided by the web service section 110of the image search server 100 in a file-upload or drag-and-drop mannerand uploads the registered search image to the image search server 100.In this case, the user can enter error information of different angles,colors, sizes and eigen values for the search image so as to select asearch by entire matching or partial matching. That is, the user candetermine an error range to perform an error-setting step for anefficient search so as to consider an arbitrary error. Such error rangeadjustment can be provided on an interface provided by the web servicesection, which is called “accuracy setting” such that the user canarbitrarily set the error range.

Thereafter, the image conversion section 120 of the image search server100 performs image conversion on the search image uploaded thereto bythe user. In this case, as described above with reference to FIGS. 1 to6, the image conversion performed in the step S22 includes the steps of:converting the image included in the searched website information into asearch format image; extracting a hash value from the converted searchformat image as an eigen value; extracting the number of unit colors andthe ratio between the unit colors as eigen values; extracting the numberof unit colors and the ratio between the unit colors at a certaincollective region as eigen values; extracting the linear/multi-linearpattern information as an eigen value; and reconstructing a reducedimage in a representative color among the colors of respective pixelsand extracting the reconstructed representative color as an eigen value.

Next, as described above, after the image conversion for theto-be-searched image uploaded by the user has been performed and theeigen values have been extracted, in the step S23, the eigen values forthe to-be-searched image uploaded by the user and the eigen values forthe image included in the website information stored in the storagesection 140 are compared with each other, and then corresponding websiteinformation is searched for and outputted based on the comparisonresult.

In this case, in step S24, the comparison between the eigen values forthe to-be-searched image uploaded by the user and the image included inthe website information for search of the website information includesthe steps of: comparing the hash values for the converted search formatimage; comparing the eigen values for the number of unit colors and theratio between the unit colors; comparing the eigen values for the numberof unit colors and the ratio between the unit colors at a certaincollective region; comparing the eigen values for thelinear/multi-linear pattern information; and comparing the eigen valuesfor the reconstructed representative color of respective pixels.

The comparison between the eigen values for the to-be-searched imageuploaded by the user and the image included in the website informationincludes an entire matching step or a partial matching step.

The website information search processing method will be described inmore detail hereinafter with reference to FIGS. 8 to 12.

First, the entire matching or the partial matching between the eigenvalues for the to-be-searched image uploaded by the user and the imageincluded in the website information refers to a step of comparing one ormore of the eigen values of the non-compression format image, or thereduced file image and the color simplified image and determiningwhether or not there is the entire matching between the compared eigenvalues or there is the partial matching between the compared eigenvalues within a certain error range.

In other words, in the entire matching determining step of the processof comparing the hash values, comparing the eigen values for the numberof unit colors and the ratio between the unit colors and comparing theeigen values for the number of unit colors and the ratio between theunit colors at a certain collective region, as shown in FIG. 9, the leftimage of two images is the to-be-searched image uploaded by the user,and the right image is the image included in the website information,which are the same as each other in terms of size and color. In thiscase, the image search of the present invention enables retrieval of thewebsite information including the to-be-searched image uploaded by theuser through the step of determining the entire matching between theeigen values. In addition, in the partial matching determining step, asshown in FIG. 10, the to-be-searched image uploaded by the user and theimage included in the website information are the same as in terms ofsize but are different from each other in terms of color due todiscoloring, etc. In this case, the website information including theimage having the eigen values within a certain error range (accuracyrange) for the matching between the eigen values is detected as thewebsite information to be searched.

Next, in the step of determining the entire matching between thelinear/multi-linear pattern information, as shown in FIG. 11, when theto-be-searched image at the left side is a part of the searched image atthe right side, a linear pattern for the to-be-searched image is set andthe eigen value for the linear pattern is generated. Then, the samelinear pattern is extracted from the searched image and the eigen valueis generated. Thereafter, the respective generated eigen values for theto-be-searched image and the searched image are compared with eachother. If the eigen values match each other, the website informationincluding a corresponding to-be-searched image is detected as thewebsite information to be searched. In the step of determining thepartial matching between the linear/multi-linear pattern information, asshown in FIG. 12, the to-be-searched image at the left side is a part ofthe searched image at the right side, and the to-be-searched image andthe searched image are different from each other in terms of color dueto discoloring, etc. In this case, a linear pattern for thecorresponding to-be-searched image is set and the eigen value for thelinear pattern is generated. Then, the same linear pattern is extractedfrom the searched image and the eigen value is generated. Thereafter,the respective generated eigen values for the to-be-searched image andthe search image are compared with each other. If the eigen values matcheach other within a certain error range, the website informationincluding a corresponding to-be-searched image is detected as thewebsite information to be searched.

Then, after the search of the website information as described above hasbeen completed, a keyword for retrieval of corresponding websiteinformation is detected from search history information for the searchedwebsite and then is annotated to the website information stored in thestorage section so as to perform a step of detecting the keyword, whichis in turn stored in the storage section. The searched keyword isoutputted to the user terminal so that the user can perform a keywordsearch for the corresponding website information (S24).

As described above, the search system using images according to thepresent invention provides advantageous effects in that even when a userwho performs information search on the Internet does not correctly knowa relevant URL or search keyword, he or she can search for informationon the Internet using an associated image to be searched.

In addition, the present invention provides further advantageous effectsin that an image owner can easily search whether or not his or her imageis used without any consent and permission of the image owner so as toprotect an image copyright.

The invention has been described in detail with reference to preferredembodiments thereof. However, it will be appreciated by those skilled inthe art that changes may be made in these embodiments without departingfrom the principles and spirit of the invention, the scope of which isdefined in the appended claims and their equivalents.

1-17. (canceled)
 18. A computer-implemented method for searching usingan image, comprising: receiving an image; determining, by a processor,at least one first eigen value for the image using a ratio between unitcolors of the image; determining, by the processor, at least one secondeigen value for the image using a degree of collection of colors of atleast a portion the image; comparing the first eigen value or the secondeigen value with an eigen value for a second image to determine whetherthe second image is a matching image for the image; and sendinginformation related to the second image.
 19. The method of claim 18,further comprising: sending a user interface to a user device, the userinterface comprising a drag-and-drop for uploading an image forsearching.
 20. The method of claim 18, further comprising: determiningat least one first eigen value for the second image using a ratiobetween unit colors of the second image; and determining at least onesecond eigen value for the second image using a degree of collection ofcolors of at least a portion of the second image, wherein comparingcomprises comparing the first eigen value or the second eigen value forthe image with the first eigen value or the second eigen value for thesecond image to determine whether the second image is a matching imagefor the image.
 21. The method of claim 18, further comprising: reducingthe image at a fixed ratio; reconstructing the image in a representativecolor based on a simplified color palette; and determining at least onethird eigen value for the reconstructed image in the representativecolor.
 22. The method of claim 18, further comprising: determining atleast one fourth eigen value for the image using a linear/multi-linearpattern between single/plural patterns.
 23. The method of claim 18,further comprising: adjusting an error range for the determining whetherthe second image is a matching image for the image.
 24. The method ofclaim 18, further comprising: determining at least one fifth eigen valuefor the image using hash values of the image.
 25. A computer program forsearching using an image, the computer program embodied in acomputer-readable medium and comprising instructions for a processor,when executed, to perform a method, the method comprising: receiving animage; determining at least one first eigen value for the image using aratio between unit colors of the image; determining at least one secondeigen value for the image using a degree of collection of colors of atleast a portion the image; comparing the first eigen value or the secondeigen value with an eigen value for a second image to determine whetherthe second image is a matching image for the image; and sendinginformation related to the second image.
 26. The computer program ofclaim 25, wherein the method further comprises: sending a user interfaceto a user device, the user interface comprising a drag-and-drop foruploading an image for searching.
 27. The computer program of claim 25,wherein the method further comprises: determining at least one firsteigen value for the second image using a ratio between unit colors ofthe second image; and determining at least one second eigen value forthe second image using a degree of collection of colors of at least aportion of the second image, wherein comparing comprises comparing thefirst eigen value or the second eigen value for the image with the firsteigen value or the second eigen value for the second image to determinewhether the second image is a matching image for the image.
 28. Thecomputer program of claim 25, wherein the method further comprises:reducing the image at a fixed ratio; reconstructing the image in arepresentative color based on a simplified color palette; anddetermining at least one third eigen value for the reconstructed imagein the representative color.
 29. The computer program of claim 25,wherein the method further comprises: determining at least one fourtheigen value for the image using a linear/multi-linear pattern betweensingle/plural patterns.
 30. The computer program of claim 25, whereinthe method further comprises: adjusting an error range for thedetermining whether the second image is a matching image for the image.31. The computer program of claim 25, wherein the method furthercomprises: determining at least one fifth eigen value for the imageusing hash values of the image.
 32. A system for searching using animage, comprising: a memory; and a processor to execute instructionsfor: receiving an image; determining, by a processor, at least one firsteigen value for the image using a ratio between unit colors of theimage; determining, by the processor, at least one second eigen valuefor the image using a degree of collection of colors of at least aportion the image; comparing the first eigen value or the second eigenvalue with an eigen value for a second image to determine whether thesecond image is a matching image for the image; and sending informationrelated to the second image.
 33. The system of claim 32, wherein theinstructions further comprise: sending a user interface to a userdevice, the user interface comprising a drag-and-drop for uploading animage for searching.
 34. The system of claim 32, wherein theinstructions further comprise: determining at least one first eigenvalue for the second image using a ratio between unit colors of thesecond image; and determining at least one second eigen value for thesecond image using a degree of collection of colors of at least aportion of the second image, wherein comparing comprises comparing thefirst eigen value or the second eigen value for the image with the firsteigen value or the second eigen value for the second image to determinewhether the second image is a matching image for the image.
 35. Thesystem of claim 32, wherein the instructions further comprise: reducingthe image at a fixed ratio; reconstructing the image in a representativecolor based on a simplified color palette; and determining at least onethird eigen value for the reconstructed image in the representativecolor.
 36. The system of claim 32, wherein the instructions furthercomprise: determining at least one fourth eigen value for the imageusing a linear/multi-linear pattern between single/plural patterns. 37.The system of claim 32, wherein the instructions further comprise:adjusting an error range for the determining whether the second image isa matching image for the image.
 38. The system of claim 32, wherein theinstructions further comprise: determining at least one fifth eigenvalue for the image using hash values of the image.